xinrong-databricks commented on code in PR #36464:
URL: https://github.com/apache/spark/pull/36464#discussion_r869454838
##########
python/pyspark/pandas/groupby.py:
##########
@@ -2121,11 +2121,22 @@ def _limit(self, n: int, asc: bool) -> FrameLike:
)
)
- sdf = (
- sdf.withColumn(tmp_col, F.row_number().over(window))
- .filter(F.col(tmp_col) <= n)
- .drop(tmp_col)
- )
+ if n >= 0 or LooseVersion(pd.__version__) < LooseVersion("1.4.0"):
+ sdf = (
+ sdf.withColumn(tmp_row_num_col, F.row_number().over(window))
+ .filter(F.col(tmp_row_num_col) <= n)
+ .drop(tmp_row_num_col)
+ )
+ else:
+ # Pandas supports Groupby positional indexing since v1.4.0
+ #
https://pandas.pydata.org/docs/whatsnew/v1.4.0.html#groupby-positional-indexing
+ tmp_cnt_col = verify_temp_column_name(sdf, "__group_count__")
+ sdf = (
+ sdf.withColumn(tmp_row_num_col, F.row_number().over(window))
+ .withColumn(tmp_cnt_col,
F.count("*").over(Window.partitionBy(*groupkey_scols)))
Review Comment:
nit:
We may also extract `Window.partitionBy(*groupkey_scols)` as a variable
since there are 3 uses in this function.
Meanwhile, renaming `window` to be more specific may help understand the
code (and see its difference from the window above).
The current code looks good enough if you prefer not to change it.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
